How low power and more intelligence can go hand in hand 

Driven by advances in silicon and machine learning algorithms, Edge AI is presenting vast opportunities for businesses across diverse markets. 

The ability to add low cost and low power intelligence onto edge IoT devices themselves is opening the door to a range of new AI-enhanced products and digital services. 

This has established Edge AI as highly complementary to cloud, pushing past some of its limitations, including: 

  • Latency – Relying on the cloud means relying on a constant connection to the cloud. Edge AI enables intelligence in low-latency and safety-critical applications. 
  • Privacy – Edge AI provides a locally processed alternative to uploading data, enabling intelligence to be applied to data too sensitive to share. 
  • Power/cost – Being always-on and always-connected often sets a minimum floor to the cost of cloud-based intelligence. Edge AI enables ultra-low cost, ultra-low power intelligent devices.  

This paper is essential reading for any business looking to bring greater levels of intelligence to the edge, unearthing the technologies and strategies that can make this a reality.

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Author
Michal Gabrielczyk
Head of Edge AI

Michal works with clients to explore how their businesses can be transformed with the right mix of cutting-edge technologies. Michal helps our customers apply Cambridge Consultants’ world-leading expertise in AI, silicon, sensing and connectivity to realise their ambitions with AI at the edge.